26E074NIO - Algorithms for Nondestructive Evaluation of Objects
| Course specification | ||||
|---|---|---|---|---|
| Course title | Algorithms for Nondestructive Evaluation of Objects | |||
| Acronym | 26E074NIO | |||
| Study programme | Electrical Engineering and Computing | |||
| Module | Information and Communication Technologies - Audio and Video Technologies, Information and Communication Technologies - Internet and Mobile Communications, Information and Communication Technologies - Microwave Technology | |||
| Type of study | bachelor academic studies | |||
| Lecturer (for classes) | ||||
| Lecturer/Associate (for practice) | ||||
| Lecturer/Associate (for OTC) | ||||
| ESPB | 6.0 | Status | elective | |
| Condition | ||||
| The goal | Course objective is to introduce students to modern algorithms for image formation of objects based on sensor data, as well as to develop practical skills for their application in engineering practice and research. | |||
| The outcome | Students will be able to understand and apply different algorithms for image reconstruction from sensor measurements across a broad frequency range to solve practical engineering problems. | |||
| Contents | ||||
| Contents of lectures | Introduction to the object examination using sensor measurements.The relationship between the physical properties of objects and sensor measurements. Adaptation of models depending on frequency. Numerical approximation of models. Inverse problems and solution stabilization. Fundamental algorithms for image reconstruction. Tikhonov regularization. Gauss-Newton method. Quality assessment metrics | |||
| Contents of exercises | Lectures are complemented by in-class demonstrations of algorithms using software tools such as MATLAB and Python, applied to examples relevant to engineering practice. As part of the course, students also work on individual projects, enabling a deeper understanding and practical application of the covered methods. | |||
| Number of hours per week during the semester/trimester/year | ||||
| Lectures | Exercises | OTC | Study and Research | Other classes |
| 3 | 1 | 1 | ||
| Methods of teaching | Lectures, demonstrations, homework, and individual projects. | |||
| Knowledge score (maximum points 100) | ||||
| Pre obligations | Points | Final exam | Points | |
| Activites during lectures | Test paper | 30 | ||
| Practical lessons | 40 | Oral examination | ||
| Projects | 30 | |||
| Colloquia | ||||
| Seminars | ||||